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Author |
Zhang, S.; Tao, F.; Zhang, Z. |
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Title |
Changes in extreme temperatures and their impacts on rice yields in southern China from 1981 to 2009 |
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Journal Article |
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Year |
2016 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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Volume |
189 |
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43-50 |
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Keywords |
Adaptation; Agriculture; Climate change; Crop; Extreme climate; Impacts; climate-change; spikelet sterility; heat-stress; crop yields; water-use; vulnerability; responses; period; CO2 |
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Abstract |
Extreme temperature impacts on field crop are of key concern and increasingly assessed, however the studies have seldom taken into account the automatic adaptations such as shifts in planting dates, phenological dynamics and cultivars. In this present study, trial data on rice phenology, agro-meteorological hazards and yields during 1981-2009 at 120 national agro-meteorological experiment stations were used. The detailed data provide us a unique opportunity to quantify extreme temperature impacts on rice yield more precisely and in a setting with automatic adaptations. In this study, changes in an accumulated thermal index (growing degree day, GDD), a high temperature stress index (>35 degrees C high temperature degree day, HDD), and a cold stress index (<20 degrees C cold degree day, CDD), were firstly investigated. Then, their impacts on rice yield were further quantified by a multivariable analysis. The results showed that in the past three decades, for early rice, late rice and single rice in western part, and single rice in other parts of the middle and lower reaches of Yangtze River, respectively, rice yield increased by 5.83%, 1.71%, 8.73% and 3.49% due to increase in GDD. Rice yield was generally more sensitive to high temperature stress than to cold temperature stress. It decreased by 0.14%, 0.32%, 0.34% and 0.14% due to increase in HDD, by contrast increased by 1.61%, 0.26%, 0.16% and 0.01% due to decrease in CDD, respectively. In addition, decreases in solar radiation reduced rice yield by 0.96%, 0.13%, 9.34% and 6.02%. In the past three decades, the positive impacts of increase in GDD and the negative impacts of decrease in solar radiation played dominant roles in determining overall climate impacts on yield. However, with climate warming in future, the positive impacts of increase in GDD and decrease in CDD will be offset by increase in HDD, resulting in overall negative climate impacts on yield. Our findings highlight the risk of heat stress on rice yield and the importance of developing integrated adaptation strategies to cope with heat stress. |
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0378-4290 |
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CropM, ft_macsur |
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MA @ admin @ |
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4731 |
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Webber, H.; Ewert, F.; Kimball, B.A.; Siebert, S.; White, J.W.; Wall, G.W.; Ottman, M.J.; Trawally, D.N.A.; Gaiser, T. |
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Title |
Simulating canopy temperature for modelling heat stress in cereals |
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Journal Article |
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Year |
2016 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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77 |
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143-155 |
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Keywords |
canopy temperature; heat stress; cereals; crop models; profile relationships; crop production; climate-change; spring wheat; field plots; growth; maize; water; yields; variability |
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Abstract |
Crop models must be improved to account for the effects of heat stress events on crop yields. To date, most approaches in crop models use air temperature to define heat stress intensity as the cumulative sum of thermal times (TT) above a high temperature threshold during a sensitive period for yield formation. However, observational evidence indicates that crop canopy temperature better explains yield reductions associated with high temperature events than air temperature does. This study presents a canopy level energy balance using Monin ObukhovSimilarity Theory (MOST) with simplifications about the canopy resistance that render it suitable for application in crop models and other models of the plant environment. The model is evaluated for a uniform irrigated wheat canopy in Arizona and rainfed maize in Burkina Faso. No single variable regression relationships for key explanatory variables were found that were consistent across sowing dates to explain the deviation of canopy temperature from air temperature. Finally, thermal times determined with simulated canopy temperatures were able to reproduce thermal times calculated with observed canopy temperature, whereas those determined with air temperatures were not. (C) 2015 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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4730 |
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Murat, M.; Malinowska, I.; Hoffmann, H.; Baranowski, P. |
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Title |
Statistical modelling of agrometeorological time series by exponential smoothing |
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Journal Article |
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2016 |
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International Agrophysics |
Abbreviated Journal |
International Agrophysics |
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30 |
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1 |
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57-65 |
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exponential smoothing; meteorological time series; statistical forecasting; daily temperature records; weighted moving averages; climate-change; prediction; forecasts; state; weather |
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Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error. |
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0236-8722 |
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CropM, ft_macsur |
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MA @ admin @ |
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4728 |
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van Bussel, L.G.J.; Stehfest, E.; Siebert, S.; Müller, C.; Ewert, F. |
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Title |
Simulation of the phenological development of wheat and maize at the global scale |
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Journal Article |
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2015 |
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Global Ecology and Biogeography |
Abbreviated Journal |
Glob. Ecol. Biogeogr. |
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24 |
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9 |
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1018-1029 |
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Agricultural management; crop calendars; cultivar; variety characteristics; global crop modelling; global harvest dates; phenology; climate-change; winter-wheat; annual crops; photoperiod sensitivity; geographical variation; temperature; responses; adaptation; cultivars; model |
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AimTo derive location-specific parameters that reflect the geographic differences among cultivars in vernalization requirements, sensitivity to day length (photoperiod) and temperature, which can be used to simulate the phenological development of wheat and maize at the global scale. LocationGlobal. Methods Based on crop calendar observations and literature describing the large-scale patterns of phenological characteristics of cultivars, we developed algorithms to compute location-specific parameters to represent this large-scale pattern. Vernalization requirements were related to the duration and coldness of winter, sensitivity to day length was assumed to be represented by the minimum and maximum day lengths occurring at a location, and sensitivity to temperature was related to temperature conditions during the vegetative development phase of the crop. Results Application of the derived location-specific parameters resulted in high agreement between simulated and observed lengths of the cropping period. Agreement was especially high for wheat, with mean absolute errors of less than 3 weeks. In the main maize cropping regions, cropping periods were over- and underestimated by 0.5-1.5 months. We also found that interannual variability in simulated wheat harvest dates was more realistic when accounting for photoperiod effects. Main conclusions The methodology presented here provides a good basis for modelling the phenological characteristics of cultivars at the global scale. We show that current global patterns of growing season length as described in cropping calendars can be largely reproduced by phenology models if location-specific parameters are derived from temperature and day length indicators. Growing seasons can be modelled more accurately for wheat than for maize, especially in warm regions. Our method for computing parameters for phenology models from temperature and day length offers opportunities to improve the simulation of crop productivity by crop simulation models developed for large spatial areas and for long-term climate impact projections that account for adaptation in the selection of varieties |
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1466-822x |
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CropM, ft_macsur |
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MA @ admin @ |
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4729 |
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Weindl, I.; Lotze-Campen, H.; Popp, A.; Müller, C.; Havlík, P.; Herrero, M.; Schmitz, C.; Rolinski, S. |
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Title |
Livestock in a changing climate: production system transitions as an adaptation strategy for agriculture |
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Journal Article |
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2015 |
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Environmental Research Letters |
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Environ. Res. Lett. |
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10 |
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9 |
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094021 |
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livestock; climate impacts; land use modeling; adaptation costs; production systems; greenhouse-gas emissions; global change; management implications; developing-countries; crop productivity; change mitigation; food security; model; impacts; carbon |
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Livestock farming is the world’s largest land use sector and utilizes around 60% of the global biomass harvest. Over the coming decades, climate change will affect the natural resource base of livestock production, especially the productivity of rangeland and feed crops. Based on a comprehensive impact modeling chain, we assess implications of different climate projections for agricultural production costs and land use change and explore the effectiveness of livestock system transitions as an adaptation strategy. Simulated climate impacts on crop yields and rangeland productivity generate adaptation costs amounting to 3% of total agricultural production costs in 2045 (i.e. 145 billion US$). Shifts in livestock production towards mixed crop-livestock systems represent a resource-and cost-efficient adaptation option, reducing agricultural adaptation costs to 0.3% of total production costs and simultaneously abating deforestation by about 76 million ha globally. The relatively positive climate impacts on grass yields compared with crop yields favor grazing systems inter alia in South Asia and North America. Incomplete transitions in production systems already have a strong adaptive and cost reducing effect: a 50% shift to mixed systems lowers agricultural adaptation costs to 0.8%. General responses of production costs to system transitions are robust across different global climate and crop models as well as regarding assumptions on CO2 fertilization, but simulated values show a large variation. In the face of these uncertainties, public policy support for transforming livestock production systems provides an important lever to improve agricultural resource management and lower adaptation costs, possibly even contributing to emission reduction. |
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1748-9326 |
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LiveM, ft_macsur |
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MA @ admin @ |
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4718 |
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