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We have studied future changes in the atmospheric and hydrological environments in Northeast Thailand from the viewpoint of risk assessment of future cultural environments in crop fields. To obtain robust and reliable estimation for future climate, ten general circulation models under three warming scenarios, B1, A1B, and A2, were used in this study. The obtained change trends show that daily maximum air temperature and precipitation will increase by 2.6°C and 4.0%, respectively, whereas soil moisture will decrease by c.a. 1% point in volumetric water content at the end of this century under the A1B scenario. Seasonal contrasts in precipitation will intensify: precipitation increases in the rainy season and precipitation decreases in the dry season. Soil moisture will slightly decrease almost throughout the year. Despite a homogeneous increase in the air temperature over Northeast Thailand, a future decrease in soil water content will show a geographically inhomogeneous distribution: Soil will experience a relative larger decrease in wetness at a shallow depth on the Khorat plateau than in the surrounding mountainous area, reflecting vegetation cover and soil texture. The predicted increase in air temperature is relatively consistent between general circulation models. In contrast, relatively large intermodel differences in precipitation, especially in long-term trends, produce unwanted bias errors in the estimation of other hydrological elements, such as soil moisture and evaporation, and cause uncertainties in projection of the agro-climatological environment. Offline hydrological simulation with a wide precipitation range is one strategy to compensate for such uncertainties and to obtain reliable risk assessment of future cultural conditions in rainfed paddy fields in Northeast Thailand. [ABSTRACT FROM AUTHOR]

Climate change, particularly rising temperatures, negatively affects rice grain quality, increasing chalky grain percentage (CG) and hampering rice grade and price. Heat-tolerant cultivars have been bred and released since the 2000 s, but the effectiveness of heat tolerance in reducing the occurrence of CG has yet to be quantified. This study aimed to measure the effectiveness of breeding for better heat tolerance in reducing the negative impact of high temperatures on rice quality. Through a systematic literature search, we developed a dataset including 1297 field observations covering 48 cultivars from five different heat tolerant ranks (HTRs) at 44 sites across Japan. A linear mixed-effect model (LME) and a random forest model (RF) were fitted to the data to analyze the effect of HTR and climatic factors such as the cumulative mean air temperature above 26 °C (TaHD), mean solar radiation, and mean relative humidity for 20 days after heading on CG. The LME model explained 63% of the variation of the whole dataset with a 14% RMSE. The RF partial dependence plot revealed that the logit-transformed CG response to climate factors was linear, supporting the assumption of the LME. The statistical analysis showed that CG increased as a function of TaHD (P < 0.001), with significant differences among HTRs (P < 0.001). The strongest effect of TaHD was obtained for the lowest HTR and was found to decrease with increasing HTR. CG also increased with higher relative humidity (P < 0.001) and solar radiation (P < 0.01). Based on our modeling, we estimated that as TaHD increased from 20 to 80 °Cd (equivalent to a mean temperature increase from 27 °C to 30 °C), CG increased by 66% points (difference in CG) for cultivars with the lowest HTR, 45% points for cultivars with an intermediate HTR, and 19% points for cultivars with the highest HTR. Raising HTR by just one step (from intermediate to moderately tolerant) is projected to increase the proportion of first-grade rice at a grain-filling temperature of 27 °C, but tolerance levels need to be improved further in case of stronger warming. The effect of high temperatures on CG was highly dependent on the cultivar's HTR. Improvements in HTR effectively reduce the negative impacts of high temperatures on rice grain quality. Heat-tolerant cultivars are projected to suppress the prevalence of CG more than threefold compared with heat-sensitive cultivars when grain-filling temperature increases from 27 to 30 °C. • The effect of cultivars' heat tolerance on rice grain quality is quantified. • A dataset of chalky grain occurrence for 48 cultivars across Japan is developed. • A statistical model accounts for about 2/3 of the chalky grain % variation. • Raising tolerance rank reduces chalky grains up to grain filling temperature of 27°C. • The model is useful for backcasting breeding targets under climate change. [ABSTRACT FROM AUTHOR]

Climate change may disrupt species–species interactions via phenological changes in one or both species. To predict and evaluate the influence of climate change on these interactions, long-term monitoring and sampling over large spatial areas are required; however, funding and labor constraints limit data collection. In this study, we predict and evaluate the plant–insect interactions with limited data sets. We examined plant–insect interaction using observational data for development of the crop plant rice (Oryza sativa) and an effective accumulated temperature (EAT) model of two mirid bugs (Stenotus rubrovittatus and Trigonotylus caelestialium). We combined 11 years of records monitoring rice phenology and the predicted phenology of mirid bugs using spatially–explicit EAT models based on both spatially and temporally high resolutions temperature data sets, then evaluated their accuracy using actual pest damage records. Our results showed that the predicted interactions between rice and mirid bugs explained rice damage to some degree. Our approach may apply predicting changes to plant–insect interactions under climate change. As such, combining plant monitoring records and theoretical predictions of insect phenology may be effective for predicting species–species interactions when available data are limited. [ABSTRACT FROM AUTHOR]

We have developed a method for estimating hourly global solar radiation (GSR) from hourly sunshine duration data. This procedure requires only hourly sunshine duration as the input data and utilizes hourly precipitation and daily snow cover as auxiliary data to classify time intervals into six cases according to weather conditions. To obtain hourly GSR using a simple algebraic form, a quadratic function of the solar elevation angle and the sunshine duration ratio is used. Daily GSR is given by a sum of hourly GSRs. We evaluated the performance of the newly developed method using data obtained at 67 meteorological stations and found that the estimated GSR is highly consistent with that observed. Hourly and daily root-mean-square misfits are approximately 0.2 MJ/m2/h (~55 W/m2) and 1.4 to 1.5 MJ/m2/day (~16 to 17 W/m2), respectively. Our classification of weather conditions is effective for reducing estimation errors, especially under cloudy skies. Since the sunshine duration is observed at more meteorological stations than GSR, the proposed new method is a powerful tool for obtaining solar radiation with hourly resolution and a dense geographical distribution. One of the proposed methods, GSRgrn, can be applicable to hourly GSR estimations at different observation sites by setting local parameters (the precipitable water, surface albedo, and atmospheric turbidity) suitable to the sites. The hourly GSR can be applied for various micrometeorological studies, such as the heat budget of crop fields. [ABSTRACT FROM AUTHOR]

The mirid bugs Stenotus rubrovittatus and Trigonotylus caelestialium, which cause pecky rice, have become a threat to rice cultivation in Asia. Damage caused by these pests has rapidly become frequent since around 2000 in Japan. Their expansion pattern is not simple, and predicting their future spread remains challenging. Some insects with wide ranges have locally adapted variations in life‐history traits. We performed laboratory rearing experiments to assess the geographical scale of intraspecific variations in life‐history traits of S. rubrovittatus and T. caelestialium. The experiments were aimed at increasing the accuracy of occurrence estimates and the number of generations per year. These results were compared with previous research, and differences in development rates were observed between populations of different latitudes, but not of the same latitude. Finally, plotting the timing of adult emergence and the potential number of generations per year on maps with a 5‐km grid revealed that they differed greatly locally at the same latitude. These maps can be used for developing more efficient methods of managing mirid bugs in integrated pest management. [ABSTRACT FROM AUTHOR]

Known as the heat-mitigation effect, irrigated rice-paddy fields distribute a large fraction of their received energy to the latent heat during the growing season. The present hypothesis is that increased atmospheric CO2 concentration decreases the stomatal conductance of rice plants and increases the air temperature by means of an increased sensible heat flux. To test this hypothesis, a coupled regional atmospheric and crop energy-balance model is developed and applied to a 300 × 300 km2 region in Japan. Downscaling meteorological variables from grid-mean values of mixed land use (3 × 3 km2) generates realistic typical diurnal cycles of air temperature in rice paddies and adjacent residential areas. The model simulation shows that, on a typical sunny day in summer, doubling the CO2 concentration increases the daily maximum grid-mean air temperature, particularly where rice paddies are present, by up to 0.7 °C. This CO2 effect on the grid-mean air temperature is approximately half the effect of the reduction in rice-paddy area that is postulated to occur on a time scale similar to that of the atmospheric CO2 change. However, within the internal atmospheric boundary layer of the rice paddies, the CO2 effect on the air temperature (+ 0.44 °C) still exceeds the effects of the land-use change (+ 0.11 °C). These results show a potentially important interplay of plant physiological responses regarding atmospheric CO2 in the heat-mitigation effect of rice-paddy fields under a changing climate. [ABSTRACT FROM AUTHOR]

There is concern about positive feedbacks between climate change and methane (CH 4 ) emission from rice paddies. However, appropriate water management may mitigate the problem. We tested this hypothesis at six field sites in central Thailand, where the irrigated area is rapidly increasing. We used DNDC-Rice, a process-based biogeochemistry model adjusted based on rice growth data at each site to simulate CH 4 emission from a rice-rice double cropping system from 2001 to 2060. Future climate change scenarios consisting of four representative concentration pathways (RCPs) and seven global climate models were generated by statistical downscaling. We then simulated CH 4 emission in three water management practices: continuous flooding (CF), single aeration (SA), and multiple aeration (MA). The adjusted model reproduced the observed rice yield and CH 4 emission well at each site. The simulated CH 4 emissions in CF from 2051 to 2060 were 5.3 to 7.8%, 9.6 to 16.0%, 7.3 to 18.0%, and 13.6 to 19.0% higher than those from 2001 to 2010 in RCPs 2.6, 4.5, 6.0, and 8.5, respectively, at the six sites. Regionally, SA and MA mitigated CH 4 emission by 21.9 to 22.9% and 53.5 to 55.2%, respectively, relative to CF among the four RCPs. These mitigation potentials by SA and MA were comparable to those from 2001 to 2010. Our results indicate that climate change in the next several decades will not attenuate the quantitative effect of water management practices on mitigating CH 4 emission from irrigated rice paddies in central Thailand. [ABSTRACT FROM AUTHOR]

Methane (CH 4 ) is a greenhouse gas, and paddy fields are one of its main anthropogenic emission sources. To mitigate this emission based on effective management measures, CH 4 emission from paddy fields must be quantified at a national scale. In Japan, country-specific emission factors have been applied since 2003 to estimate national CH 4 emission from paddy fields. However, this method cannot account for the effects of weather conditions and temporal variability of nitrogen fertilizer and organic matter application rates; thus, the estimated emission is highly uncertain. To improve the accuracy of national-scale estimates, we calculated country-specific emission factors using the DeNitrification–DeComposition-Rice (DNDC-Rice) model. First, we calculated CH 4 emission from 1981 to 2010 using 986 datasets that included soil properties, meteorological data, and field management data. Using the simulated site-specific emission, we calculated annual mean emission for each of Japan's seven administrative regions, two water management regimes (continuous flooding and conventional mid-season drainage), and three soil drainage rates (slow, moderate, and fast). The mean emission was positively correlated with organic carbon input to the field, and we developed linear regressions for the relationships among the regions, water management regimes, and drainage rates. The regression results were within the range of published observation values for site-specific relationships between CH 4 emission and organic carbon input rates. This suggests that the regressions provide a simplified method for estimating CH 4 emission from Japanese paddy fields, though some modifications can further improve the estimation accuracy. [ABSTRACT FROM AUTHOR]

Reliable regional-scale representation of crop growth and yields has been increasingly important in earth system modeling for the simulation of atmosphere-vegetation-soil interactions in managed ecosystems. While the parameter values in many crop models are location specific or cultivar specific, the validity of such values for regional simulation is in question. We present the scale dependency of likely parameter values that are related to the responses of growth rate and yield to temperature, using the paddy rice model applied to Japan as an example. For all regions, values of the two parameters that determine the degree of yield response to low temperature (the base temperature for calculating cooling degree days and the curvature factor of spikelet sterility caused by low temperature) appeared to change relative to the grid interval. Two additional parameters (the air temperature at which the developmental rate is half of the maximum rate at the optimum temperature and the value of developmental index at which point the crop becomes sensitive to the photoperiod) showed scale dependency in a limited region, whereas the remaining three parameters that determine the phenological characteristics of a rice cultivar and the technological level show no clear scale dependency. These results indicate the importance of using appropriate parameter values for the spatial scale at which a crop model operates. We recommend avoiding the use of location-specific or cultivar-specific parameter values for regional crop simulation, unless a rationale is presented suggesting these values are insensitive to spatial scale. [ABSTRACT FROM AUTHOR]

Aim Recent changes in crop yields have implications for future global food security, which are likely to be affected by climate change. We developed a spatially explicit global dataset of historical yields for maize, soybean, rice and wheat to explore the historical changes in mean, year-to-year variation and annual rate of change in yields for the period 1982-2006. Location This study was conducted at the global scale. Methods We modelled historical and spatial patterns of yields at a grid size of 1.125° by combining global agricultural datasets related to the crop calendar and harvested area in 2000, country yield statistics and satellite-derived net primary production. Modelled yields were compared with other global datasets of yields in 2000 ( M3-Crops and Map SPAM) and subnational yield statistics for 23 major crop-producing countries. Historical changes in modelled yields were then examined. Results Modelled yields explained 45-81% of the spatial variation of yields in 2000 from M3-Crops and Map SPAM, with root-mean-square errors of 0.5-1.8 t ha−1. Most correlation coefficients between modelled yield time series and subnational yield statistics for the period 1982-2006 in major crop-producing regions were greater than 0.8. Our analysis corroborated the incidence of reported yield stagnations and collapses and showed that low and mid latitudes in the Southern Hemisphere (0-40° S) experienced significantly increased year-to-year variation in maize, rice and wheat yields in 1994-2006 compared with that in 1982-93. Main conclusions Our analyses revealed increased instability of yields across a broad region of the Southern Hemisphere, where many developing countries are located. Such changes are likely to be related to recent yield stagnation and collapses. Although our understanding of the impacts of recent climate change, particularly the incidence of climate extremes, on crop yields remains limited, our dataset offers opportunities to close parts of this knowledge gap. [ABSTRACT FROM AUTHOR]