Lehtonen, H., Palosuo, T., Korhonen, P., & Liu, X. (2018). Higher Crop Yield Levels in the North Savo Region—Means and Challenges Indicated by Farmers and Their Close Stakeholders. Agriculture, 8(7), 93.
Abstract: The sustainable intensification of farming systems is expected to increase food supply and reduce the negative environmental effects of agriculture. It is also seen as an effective adaptation and mitigation strategy in response to climate change. Our aim is to determine farmers’ and other stakeholders’ views on how higher crop yields can be achieved from their currently low levels. This was investigated in two stakeholder workshops arranged in North Savo, Finland, in 2014 and 2016. The workshop participants, who were organized in discussion groups, considered some agricultural policies to discourage the improvement of crop yields. Policy schemes were seen to support extensification and reduce the motivation for yield improvements. However, the most important means for higher crop yields indicated by workshop participants were improved soil conditions with drainage and liming, in addition to improved crop rotations, better sowing techniques, careful selection of cultivars and forage grass mixtures. Suggested solutions for improving both crop yields and farm income also included optimized use of inputs, focusing production at the most productive fields and actively developed farming skills and knowledge sharing. These latter aspects were more pronounced in 2016, suggesting that farmers’ skills are increasingly being perceived as important.
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Asseng, S., Ewert, F., Rosenzweig, C., Jones, J. W., Hatfield, J. L., Ruane, A. C., et al. (2013). Uncertainty in simulating wheat yields under climate change. Nat. Clim. Change, 3(9), 827–832.
Abstract: Projections of climate change impacts on crop yields are inherently uncertain(1). Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate(2). However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models(1,3) are difficult(4). Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.
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Asseng, S., Ewert, F., Martre, P., Rötter, R. P., Lobell, D. B., Cammarano, D., et al. (2014). Rising temperatures reduce global wheat production. Nat. Clim. Change, 5(2), 143–147.
Abstract: Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.
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Liu, B., Asseng, S., Müller, C., Ewert, F., Elliott, J., Lobell, D. B., et al. (2016). Similar estimates of temperature impacts on global wheat yield by three independent methods. Nat. Clim. Change, 6(12), 1130–1136.
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Nendel, C., Ewert, F., Rötter, R. P., Rosenzweig, C., Jones, J. W., Hatfield, J. L., et al. (2013). Addressing challenges and uncertainties for, the use of agro-ecosystem models to, assess climate change impact and food security across scales..
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