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Eza, U., Shtiliyanova, A., Borras, D., Bellocchi, G., Carrère, P., & Martin, R. (2015). An open platform to assess vulnerabilities to climate change: An application to agricultural systems. Ecological Informatics, 30, 389–396.
Abstract: Numerous climate futures are now available from global climate models. Translation of climate data such as precipitation and temperatures into ecologically meaningful outputs for managers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platform includes a simulation modeling engine and is suited to work with NetCDF format of input and output files. In a case study covering a region (Auvergne) in the Massif Central of France, the platform is configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks. (C) 2015 Elsevier B.V. All rights reserved.
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Fan, F., Henriksen, C. B., & Porter, J. (2018). Long-term effects of conversion to organic farming on ecosystem services – a model simulation case study and on-farm case study in Denmark. Agroecology and Sustainable Food Systems, 42(5), 504–529.
Abstract: Organic agriculture aims to produce food while establishing an ecological balance to augment ecosystem services (ES) and has been rapidly expanding in the world since the 1980s. Recently, however, in several European countries, including Denmark, organic farmers have converted back to conventional farming. Hence, understanding how agricultural ES are affected by the number of years since conversion to organic farming is imperative for policy makers to guide future agricultural policy. In order to investigate the long-term effects of conversion to organic farming on ES we performed i) a model simulation case study by applying the Daisy model to simulate 14 different conversion scenarios for a Danish farm during a 65 year period with increasing number of years under organic farming, and ii) an on-farm case study in Denmark with one conventional farm, one organic farm under conversion, and three organic farms converted 10, 15 and 58 years ago, respectively. Both the model simulation case study and the on-farm case study showed that non-marketable ES values increased with increasing number of years under organic farming. Trade-offs between marketable and non-marketable ES were not evident, since also marketable ES values generally showed an increasing trend, except when the price difference between organic and conventional products in the model simulation study was the smallest, and when an alfalfa pre-crop in the on-farm case study resulted in a significantly higher level of plant available nitrogen, which boosted the yield and the associated marketable ES of the subsequent winter rye crop. These results indicate a possible benefit of preserving long-term organic farms and could be used to argue for agricultural policy interventions to offset further reduction in the number of organic farms or the land area under organic farming.
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Faye, B., Webber, H., Naab, J. B., MacCarthy, D. S., Adam, M., Ewert, F., et al. (2018). Impacts of 1.5 versus 2.0 degrees C on cereal yields in the West African Sudan Savanna. Environ. Res. Lett., 13(3), 034014.
Abstract: To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 degrees C above pre-industrial levels, with the ambition to keep warming to 1.5 degrees C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 degrees C versus 2.0 degrees C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 degrees C compared to 1.5 degrees C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security.
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Ferrise, R., Toscano, P., Pasqui, M., Moriondo, M., Primicerio, J., Semenov, M. A., et al. (2015). Monthly-to-seasonal predictions of durum wheat yield over the Mediterranean Basin. Clim. Res., 65, 7–21.
Abstract: Uncertainty in weather conditions for the forthcoming growing season influences farmers’ decisions, based on their experience of the past climate, regarding the reduction of agricultural risk. Early within-season predictions of grain yield can represent a great opportunity for farmers to improve their management decisions and potentially increase yield and reduce potential risk. This study assessed 3 methods of within-season predictions of durum wheat yield at 10 sites across the Mediterranean Basin. To assess the value of within-season predictions, the model SiriusQuality2 was used to calculate wheat yields over a 9 yr period. Initially, the model was run with observed daily weather to obtain the reference yields. Then, yield predictions were calculated at a monthly time step, starting from 6 mo before harvest, by feeding the model with observed weather from the beginning of the growing season until a specific date and then with synthetic weather constructed using the 3 methods, historical, analogue or empirical, until the end of the growing season. The results showed that it is possible to predict durum wheat yield over the Mediterranean Basin with an accuracy of normalized root means squared error of <20%, from 5 to 6 mo earlier for the historical and empirical methods and 3 mo earlier for the analogue method. Overall, the historical method performed better than the others. Nonetheless, the analogue and empirical methods provided better estimations for low-yielding and high-yielding years, thus indicating great potential to provide more accurate predictions for years that deviate from average conditions.
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Foyer, C. H., Siddique, K. H. M., Tai, A. P. K., Anders, S., Fodor, N., Wong, F. - L., et al. (2019). Modelling predicts that soybean is poised to dominate crop production across Africa. Plant Cell Environ., 42(1), 373–385.
Abstract: The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume-based farming is particularly important in Africa, where small-scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land-use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful “soybean bonanza” across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.
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