|
|
Tao, F., Zhang, S., Zhang, Z., & Rötter, R. P. (2015). Temporal and spatial changes of maize yield potentials and yield gaps in the past three decades in China. Agric. Ecosyst. Environ., 208, 12–20.
Abstract: The precise spatially explicit knowledge about crop yield potentials and yield gaps is essential to guide sustainable intensification of agriculture. In this study, the maize yield potentials from 1980 to 2008 across the major maize production regions of China were firstly estimated by county using ensemble simulation of a well-validated large scale crop model, i.e., MCWLA-Maize model. Then, the temporal and spatial patterns of maize yield potentials and yield gaps during 1980-2008 were presented and analyzed. The results showed that maize yields became stagnated at 32.4% of maize-growing areas during the period. In the major maize production regions, i.e., northeastern China, the North China Plain (NCP) and southwestern China, yield gap percentages were generally less than 40% and particularly less than 20% in some areas. By contrast, in northern and southern China, where actual yields were relatively lower, yield gap percentages were generally larger than 40%. The areas with yield gap percentages less than 20% and less than 40% accounted for 8.2% and 27.6% of maize-growing areas, respectively. During the period, yield potentials decreased in the NCP and southwestern China due to increase in temperature and decrease in solar radiation; by contrast, increased in northern, northeastern and southeastern China due to increases in both temperature and solar radiation. Yield gap percentages decreased generally by 2% per year across the major maize production regions, although increased in some areas in northern and northeastern China. The shrinking of yield gap was due to increases in actual yields and decreases in yield potentials in the NCP and southwestern China; and due to larger increases in actual yields than in yield potentials in northeastern and southeastern China. The results highlight the importance of sustainable intensification of agriculture to close yield gaps, as well as breeding new cultivars to increase yield potentials, to meet the increasing food demand. (C) 2015 Elsevier B.V. All rights reserved.
|
|
|
|
Kim, Y., Seo, Y., Kraus, D., Klatt, S., Haas, E., Tenhunen, J., et al. (2015). Estimation and mitigation of N₂O emission and nitrate leaching from intensive crop cultivation in the Haean catchment, South Korea. Science of the Total Environment, 529, 40–53.
Abstract: Considering intensive agricultural management practices and environmental conditions, the LandscapeDNDC model was applied for simulation of yields, N2O emission and nitrate leaching from major upland crops and temperate deciduous forest of the Haean catchment, South Korea. Fertilization rates were high (up to 314 kg N ha(-1) year(-1)) and resulted in simulated direct N2O emissions from potato, radish, soybean and cabbage fields of 1.9 and 2.1 kg N ha(-1) year(-1) in 2009 and 2010, respectively. Nitrate leaching was identified as the dominant pathway of N losses in the Haean catchment with mean annual rates of 112.2 and 125.4 kg N ha(-1) year(-1), causing threats to water quality and leading to substantial indirect N2O emissions of 0.84 and 0.94 kg N ha(-1) year(-1) in 2009 and 2010 as estimates by applying the IPCC EF5. Simulated N2O emissions from temperate deciduous forest were low (approx. 0.50 kg N ha(-1) year(-1)) and predicted nitrate leaching rates were even negligible (≤0.01 kg N ha(-1) year(-1)). On catchment scale more than 50% of the total N2O emissions and up to 75% of nitrate leaching originated from fertilized upland fields, only covering 24% of the catchment area. Taking into account area coverage of simulated upland crops and other land uses these numbers agree well with nitrate loads calculated from discharge and concentration measurements at the catchment outlet. The change of current agricultural management practices showed a high potential of reducing N2O emission and nitrate leaching while maintaining current crop yields. Reducing (39%) and splitting N fertilizer application into 3 times was most effective and lead to about 54% and 77% reducing of N2O emission and nitrate leaching from the Haean catchment, the latter potentially contributing to improved water quality in the Soyang River Dam, which is the major source of drinking water for metropolitan residents.
|
|
|
|
Ewert, F., Rötter, R. P., Bindi, M., Webber, H., Trnka, M., Kersebaum, K. C., et al. (2015). Crop modelling for integrated assessment of risk to food production from climate change. Env. Model. Softw., 72, 287–303.
Abstract: The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches.
|
|
|
|
Schauberger, B., Rolinski, S., & Müller, C. (2016). A network-based approach for semi-quantitative knowledge mining and its application to yield variability. Environ. Res. Lett., 11(12), 123001.
Abstract: Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. Asystematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.
|
|
|
|
Himanen, S. J., Ketoja, E., Hakala, K., Rötter, R. P., Salo, T., & Kahiluoto, H. (2013). Cultivar diversity has great potential to increase yield for feed barley. Agron. Sust. Developm., 33(3), 519–530.
Abstract: This study shows an average yield increase of 415–1,338 kg ha−1 per unit increase of the Shannon diversity index for feed barley cultivar use. There is a global quest to increase food production sustainably. Therefore, judicious farmer choices such as selection of crop cultivars are increasingly important. Cultivar diversity is limited and, as a consequence, corresponding crop yields are highly impacted by local weather variations and global climate change. Actually, there is little knowledge on the relationships between yields of regional crops and cultivar diversity, that is evenness and richness in cultivar use. Here, we hypothesized that higher cultivar diversity is related to higher regional yield. We also assumed that the diversity-yield relationship depends on weather during the growing season. Our data were based on farm yield surveys of feed and malting barley, Hordeum vulgare L.; spring wheat, Triticum aestivum L.; and spring turnip rape, Brassica rapa L. ssp. oleifera, from 1998 to 2009, representing about 4,500–5,500 farms annually. We modeled the relationships between regional yields and Shannon diversity indices in high-yielding (south-west) and low-yielding (central-east) regions of Finland using linear mixed models. Our results show that an increase of Shannon diversity index increases yield of feed barley. Feed barley had also the greatest cultivar diversity. In contrast, an average yield decrease of 1,052 kg ha−1 per unit increase in Shannon index was found for spring rape in 2006 and 2008. Our findings show that cultivar diversification has potential to raise mean regional yield of feed barley. Increasing cultivar diversity thus offers a novel, sustainability-favoring means to promote higher yields.
|
|
