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Zhang, S., Tao, F., & Zhang, Z. (2017). Uncertainty from model structure is larger than that from model parameters in simulating rice phenology in China. Europ. J. Agron., 87, 30–39.
Abstract: Rice models have been widely used in simulating and predicting rice phenology in contrasting climate zones, however the uncertainties from model structure (different equations or models) and/or model parameters were rarely investigated. Here, five rice phenological models/modules (Le., CERES-Rice, ORYZA2000, RCM, Beta Model and SIMRIW) were applied to simulate rice phenology at 23 experimental stations from 1992 to 2009 in two major rice cultivation regions of China: the northeastern China and the southwestern China. To investigate the uncertainties from model biophysical parameters, each model was run with randomly perturbed 50 sets of parameters. The results showed that the median of ensemble simulations were better than the simulation by most models. Models couldn’t simulate well in some specific years despite of parameters optimization, suggesting model structure limit model performance in some cases. The models adopting accumulative thermal time function (e.g., CERES-Rice and ORYZA2000) had better performance in the southwestern China, in contrast, those adopting exponential function (e.g., Beta model and RCM model) had better performance in the northeastern China. In northeastern China, the contribution of model structure and model parameters to model total variance was, respectively, about 55.90% and 44.10% in simulating heading date, and about 75.43% and 24.57% in simulating maturity date. In the southwestern China, the contribution of model structure and model parameters to model total variance was, respectively, about 79.97% and 27.03% in simulating heading date, about 92.15% and 7.85% in simulating maturity date. Uncertainty from model structure was the most relevant source. The results highlight that the temperature response functions of rice development rate under extreme climate conditions should be improved based on environment-controlled experimental data.
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Schils, R., Olesen, J. E., Kersebaum, K. - C., Rijk, B., Oberforster, M., Kalyada, V., et al. (2018). Cereal yield gaps across Europe. Europ. J. Agron., 101, 109–120.
Abstract: Europe accounts for around 20% of the global cereal production and is a net exporter of ca. 15% of that production. Increasing global demand for cereals justifies questions as to where and by how much Europe’s production can be increased to meet future global market demands, and how much additional nitrogen (N) crops would require. The latter is important as environmental concern and legislation are equally important as production aims in Europe. Here, we used a country-by-country, bottom-up approach to establish statistical estimates of actual grain yield, and compare these to modelled estimates of potential yields for either irrigated or rainfed conditions. In this way, we identified the yield gaps and the opportunities for increased cereal production for wheat, barley and maize, which represent 90% of the cereals grown in Europe. The combined mean annual yield gap of wheat, barley, maize was 239 Mt, or 42% of the yield potential. The national yield gaps ranged between 10 and 70%, with small gaps in many north-western European countries, and large gaps in eastern and south-western Europe. Yield gaps for rainfed and irrigated maize were consistently lower than those of wheat and barley. If the yield gaps of maize, wheat and barley would be reduced from 42% to 20% of potential yields, this would increase annual cereal production by 128 Mt (39%). Potential for higher cereal production exists predominantly in Eastern Europe, and half of Europe’s potential increase is located in Ukraine, Romania and Poland. Unlocking the identified potential for production growth requires a substantial increase of the crop N uptake of 4.8 Mt. Across Europe, the average N uptake gaps, to achieve 80% of the yield potential, were 87, 77 and 43 kg N ha(-1) for wheat, barley and maize, respectively. Emphasis on increasing the N use efficiency is necessary to minimize the need for additional N inputs. Whether yield gap reduction is desirable and feasible is a matter of balancing Europe’s role in global food security, farm economic objectives and environmental targets.
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Cirillo, V., Masin, R., Maggio, A., & Zanin, G. (2018). Crop-weed interactions in saline environments. Europ. J. Agron., 99, 51–61.
Abstract: Soil salinization is one of the most critical environmental factors affecting crop yield. It is estimated that 20% of cultivated land and 33% of irrigated agricultural land are affected by salinity. In the last decades, considerable effort to manage saline agro-ecosystems has focused on 1) controlling soil salinity to minimize/reduce the accumulation of salts in the root zone and 2) improving plants ability to cope with osmotic and ionic stress. Less attention has been given to other components of the agro-ecosystem including weed populations, which also react and adapt to soil salinization and indirectly affect plant growth and yield. Weeds represent an increasing challenge for crop systems since they have high genetic resilience and adaptation ability to adverse environmental conditions such as soil salinization. In this review, we assess current knowledge on salinity tolerance of weeds in agricultural contexts and discuss critical components of crop-weed interactions that may increase weeds competitiveness under salinity. Compared to crop species, weeds generally exhibit greater salt tolerance due to high intraspecific variability, associated with diverse physiological adaptation mechanisms (e.g. phenotipic plasticity, seed heteromorphism, allelopathy). Weed competitiveness in saline soils may be enhanced by their earlier emergence, faster growth rates and synergies occurring between soil salts and allelochemicals released by weeds. In the future, a better understanding of crop-weed relationships and molecular, physiological and agronomic stress responses under salinity is essential to design efficient strategies to achieve weed control under altered climatic and environmental conditions.
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Tao, F., Roetter, R. P., Palosuo, T., Diaz-Ambrona, C. G. H., Ines Minguez, M., Semenov, M. A., et al. (2017). Designing future barley ideotypes using a crop model ensemble. Europ. J. Agron., 82, 144–162.
Abstract: Climate change and its associated higher frequency and severity of adverse weather events require genotypic adaptation. Process-based ecophysiological modelling offers a powerful means to better target and accelerate development of new crop cultivars. Barley (Hordeum vulgare L) is an important crop throughout the world, and a good model for study of the genetics of stress adaptation because many quantitative trait loci and candidate genes for biotic and abiotic stress tolerance have been identified in it. Here, we developed a new approach to design future crop ideotypes using an ensemble of eight barley simulation models (i.e. APSIM, CropSyst, HERMES, MCWLA, MONICA, SIMPLACE, Sirius Quality, and WOFOST), and applied it to design climate-resilient barley ideotypes for Boreal and Mediterranean climatic zones in Europe. The results showed that specific barley genotypes, represented by sets of cultivar parameters in the crop models, could be promising under future climate change conditions, resulting in increased yields and low inter-annual yield variability. In contrast, other genotypes could result in substantial yield declines. The most favorable climate-zone-specific barley ideotypes were further proposed, having combinations of several key genetic traits in terms of phenology, leaf growth, photosynthesis, drought tolerance, and grain formation. For both Boreal and Mediterranean climatic zones, barley ideotypes under future climatic conditions should have a longer reproductive growing period, lower leaf senescence rate, larger radiation use efficiency or maximum assimilation rate, and higher drought tolerance. Such characteristics can produce substantial positive impacts on yields under contrasting conditions. Moreover, barley ideotypes should have a low photoperiod and high vernalization sensitivity for the Boreal climatic zone; for the Mediterranean, in contrast, it should have a low photoperiod and low vernalization sensitivity. The drought-tolerance trait is more beneficial for the Mediterranean than for the Boreal climatic zone. Our study demonstrates a sound approach to design future barley ideotypes based on an ensemble of well-tested, diverse crop models and on integration of knowledge from multiple disciplines. The robustness of model-aided ideotypes design can be further enhanced by continuously improving crop models and enhancing information exchange between modellers, agro-meteorologists, geneticists, physiologists, and plant breeders. (C) 2016 Elsevier B.V. All rights reserved.
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Kuhnert, M., Yeluripati, J., Smith, P., Hoffmann, H., van Oijen, M., Constantin, J., et al. (2016). Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands. European Journal of Agronomy, 88, 41–52.
Abstract: For spatial crop and agro-systems modelling, there is often a discrepancy between the scale of measured driving data and the target resolution. Spatial data aggregation is often necessary, which can introduce additional uncertainty into the simulation results. Previous studies have shown that climate data aggregation has little effect on simulation of phenological stages, but effects on net primary production (NPP) might still be expected through changing the length of the growing season and the period of grain filling. This study investigates the impact of spatial climate data aggregation on NPP simulation results, applying eleven different models for the same study region (∼34,000 km2), situated in Western Germany. To isolate effects of climate, soil data and management were assumed to be constant over the entire study area and over the entire study period of 29 years. Two crops, winter wheat and silage maize, were tested as monocultures. Compared to the impact of climate data aggregation on yield, the effect on NPP is in a similar range, but is slightly lower, with only small impacts on averages over the entire simulation period and study region. Maximum differences between the five scales in the range of 1–100 km grid cells show changes of 0.4–7.8% and 0.0–4.8% for wheat and maize, respectively, whereas the simulated potential NPP averages of the models show a wide range (1.9–4.2 g C m−2 d−1 and 2.7–6.1 g C m−2 d−1for wheat and maize, respectively). The impact of the spatial aggregation was also tested for shorter time periods, to see if impacts over shorter periods attenuate over longer periods. The results show larger impacts for single years (up to 9.4% for wheat and up to 13.6% for maize). An analysis of extreme weather conditions shows an aggregation effect in vulnerability up to 12.8% and 15.5% between the different resolutions for wheat and maize, respectively. Simulations of NPP averages over larger areas (e.g. regional scale) and longer time periods (several years) are relatively insensitive to climate data.
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