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Milford, A. B., Le Mouel, C., Bodirsky, B. L., & Rolinski, S. (2019). Drivers of meat consumption. Appetite, 141, Unsp 104313.
Abstract: Increasing global levels of meat consumption are a threat to the environment and to human health. To identify measures that may change consumption patterns towards more plant-based foods, it is necessary to improve our understanding of the causes behind the demand for meat. In this paper we use data from 137 different countries to identify and assess factors that influence meat consumption at the national level using a cross-country multivariate regression analysis. We specify either total meat or ruminant meat as the dependent variable and we consider a broad range of potential drivers of meat consumption. The combination of explanatory variables we use is new for this type of analysis. In addition, we estimate the relative importance of the different drivers. We find that income per capita followed by rate of urbanisation are the two most important drivers of total meat consumption per capita. Income per capita and natural endowment factors are major drivers of ruminant meat consumption per capita. Other drivers are Western culture, Muslim religion, female labour participation, economic and social globalisation and meat prices. The main identified drivers of meat demand are difficult to influence through direct policy intervention. Thus, acting indirectly on consumers’ preferences and consumption habits (for instance through information, education policy and increased availability of ready-made plant based products) could be of key importance for mitigating the rise of meat consumption per capita all over the world.
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Constantin, J., Raynal, H., Casellas, E., Hoffman, H., Bindi, M., Doro, L., et al. (2019). Management and spatial resolution effects on yield and water balance at regional scale in crop models. Agricultural and Forest Meteorology, 275, 184–195.
Abstract: Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia ((similar to)34 083 km(2)), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 x 1 km to 100 x 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (< 10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale.
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Sanz-Cobena, A., Misselbrook, T. H., Hernaiz, P., & Vallejo, A. (2019). Impact of rainfall to the effectiveness of pig slurry shallow injection method for NH3 mitigation in a Mediterranean soil. Atm. Environ., 216, 116913.
Abstract: Ammonia emission from fertilized cropping systems is an important concern for stakeholders, particularly in regions with high livestock densities producing large amounts of manure. Application of pig slurries can result in very large losses of N through NH3 volatilization, thus decreasing the N use efficiency (NUE) of the applied manure. Shallow incorporation has been shown to significantly abate these losses. In this field study, we assessed the impact of contrasting weather conditions on the effectiveness of shallow injection to abate NH3 emissions from pig slurry application to a Mediterranean soil. As potential trade-offs of NH3 abatement, greenhouse gas emissions were also measured under conditions of high soil moisture. Compared with surface application of slurry, shallow injection effectively and significantly decreased NH3 losses independently of weather conditions, but reductions of NH3 emission were greater after heavy rainfall. In contrast, under these conditions, shallow injection triggered higher emissions of N2O and CH4. Our findings reinforce the idea that any single-pollutant abatement strategy needs to be designed and assessed in a regional context and considering potential trade-offs in the form of other pollutants.
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