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Rötter, R. P., Höhn, J. G., & Fronzek, S. (2012). Projections of climate change impacts on crop production: A global and a Nordic perspective. Acta Agriculturae Scandinavica, Section A – Animal Science, 62(4), 166–180.
Abstract: Global climate is changing and food production is very sensitive to weather and climate variations. Global assessments of climate change impacts on food production have been made since the early 1990s, initially with little attention to the uncertainties involved. Although there has been abundant analysis of uncertainties in future greenhouse gas emissions and their impacts on the climate system, uncertainties related to the way climate change projections are scaled down as appropriate for different analyses and in modelling crop responses to climate change, have been neglected. This review paper mainly addresses uncertainties in crop impact modelling and possibilities to reduce them. We specifically aim to (i) show ranges of projected climate change-induced impacts on crop yields, (ii) give recommendations on use of emission scenarios, climate models, regionalization and ensemble crop model simulations for different purposes and (iii) discuss improvements and a few known unknowns’ affecting crop impact projections.
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Reidsma, P., Wolf, J., Kanellopoulos, A., Schaap, B. F., Mandryk, M., Verhagen, J., et al. (2015). Climate change impact and adaptation research requires integrated assessment and farming systems analysis: a case study in the Netherlands. Environ. Res. Lett., 10(4), 045004.
Abstract: Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on integrated assessment and farming systems analysis, and account for adaptation at different levels. With a case study for Flevoland, the Netherlands, we illustrate that (1) crop models cannot account for all relevant climate change impacts and adaptation options, and (2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semiquantitative and participatory method assessing impacts of extreme events shows that there are nevertheless several climate risks. A range of adaptation measures are, however, available to reduce possible negative effects at crop level. In addition, at farm level farmers can change cropping patterns, and adjust inputs and outputs. Also farm structural change will influence impacts and adaptation. While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at crop and farm level, impacts may be less negative in some regions and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world.
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Reidsma, P., Wolf, J., Kanellopoulos, A., Schaap, B. F., Mandryk, M., Verhagen, J., et al. (2015). Climate change impact and adaptation research requires integrated assessment and farming systems analysis: a case study in the Netherlands. Environ. Res. Lett., 10(4), 045004.
Abstract: Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on integrated assessment and farming systems analysis, and account for adaptation at different levels. With a case study for Flevoland, the Netherlands, we illustrate that (1) crop models cannot account for all relevant climate change impacts and adaptation options, and (2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semi-quantitative and participatory method assessing impacts of extreme events shows that there are nevertheless several climate risks. A range of adaptation measures are, however, available to reduce possible negative effects at crop level. In addition, at farm level farmers can change cropping patterns, and adjust inputs and outputs. Also farm structural change will influence impacts and adaptation. While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at crop and farm level, impacts may be less negative in some regions and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world.
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Rusu, T. (2014). Energy efficiency and soil conservation in conventional, minimum tillage and no-tillage. International Soil and Water Conservation Research, 2(4), 42–49.
Abstract: The objective of this research was to determine the capacity of a soil tillage system in soil conservation, in productivity and in energy efficiency. The minimum tillage and no-tillage systems represent good alternatives to the conventional (plough) system of soil tillage, due to their conservation effects on soil and to the good production of crops (Maize, 96%-98% of conventional tillage for minimum tillage, and 99.8% of conventional tillage for no till; Soybeans, 103%-112% of conventional tillage for minimum tillage and 117% of conventional tillage for no till; Wheat, 93%-97% of conventional tillage for minimum tillage and 117% of conventional tillage for no till. The choice of the right soil tillage system for crops in rotation help reduce energy consumption, thus for maize: 97%-98% energy consumption of conventional tillage when using minimum tillage and 91% when using no-tillage; for soybeans: 98% energy consumption of conventional tillage when using minimum tillage and 93 when using no-tillage; for wheat: 97%-98% energy consumption of conventional tillage when using minimum tillage and 92% when using no-tillage. Energy efficiency is in relation to reductions in energy use, but also might include the efficiency and impact of the tillage system on the cultivated plant. For all crops in rotation, energy efficiency (energy produced from 1 MJ consumed) was the best in no-tillage — 10.44 MJ ha− 1 for maize, 6.49 MJ ha− 1 for soybean, and 5.66 MJ ha− 1 for wheat. An analysis of energy-efficiency in agricultural systems includes the energy consumed-energy produced-energy yield comparisons, but must be supplemented by soil energy efficiency, based on the conservative effect of the agricultural system. Only then will the agricultural system be sustainable, durable in agronomic, economic and ecological terms. The implementation of minimum and no-tillage soil systems has increased the organic matter content from 2% to 7.6% and water stable aggregate content from 5.6% to 9.6%, at 0–30 cm depth, as compared to the conventional system. Accumulated water supply was higher (with 12.4%-15%) for all minimum and no-tillage systems and increased bulk density values by 0.01%-0.03% (no significant difference) While the soil fertility and the wet aggregate stability have initially been low, the effect of conservation practices on the soil characteristics led to a positive impact on the water permeability in the soil. Availability of soil moisture during the crop growth period led to a better plant watering condition. Subsequent release of conserved soil water regulated the plant water condition and soil structure.
Keywords: No-tillage; Minimum tillage; Yield; Energy efficiency; Soil conservation
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Dumont, B., Basso, B., Leemans, V., Bodson, B., Destain, J. - P., & Destain, M. - F. (2015). Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions. Precision Agric., 16(4), 361–384.
Abstract: At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution.
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