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The changing climate makes it more difficult to manage water resources and food production sustainably. Various adaptation measures have been proposed to moderate the negative impacts of climate change; however, implementation of these measures may be hampered by other factors even if the benefits are acknowledged—a situation termed "soft adaptation limits" by the IPCC. We hypothesized that societal rules can be a potential barrier to adaptive action if they are too fixed, because such rules have coevolved with the interactions between the past climate and human activities. To test this hypothesis, we present a framework based on the assumption that associated societal rules of Japan's matured irrigation systems are potential barriers to adaptation. The framework consisted of two process‐based models, one to evaluate the water deficit risk and one to evaluate the benefits of optimizing rice yield and quality. We applied each model to an experiment in which we shifted the current transplantation date by 1 week for up to 5 weeks before and after the current date under the historical (1981–2000) and RCP 2.6 and 8.5 (2011–2030 and 2031–2050) scenarios. We revealed two contrasting development pathways in the study watershed. Soft adaptation limits imposed by water availability will occur by 2030 if farmers optimize for quality, whereas mutual benefits to farmers and river administrators will be achieved if farmers seek yield. We argue that more participatory research with stakeholder engagement, as well as policy discussions about these possible developments, is needed to ensure successful adaptation. Key Points: We present a framework for examining whether societal rules of Japan's matured irrigation systems are potential barriers to adaptationWe show that potential barriers to adaptation imposed by water availability will occur if farmers optimize for rice qualityWe argue that more participatory research with stakeholder engagement is needed to ensure successful adaptation [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]

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]

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]

We developed a dataset of local-scale daily climate change scenarios for Japan (called ELPIS-JP) using the stochastic weather generators (WGs) LARS-WG and, in part, WXGEN. The ELPIS-JP dataset is based on the observed (or estimated) daily weather data for seven climatic variables (daily mean, maximum and minimum temperatures; precipitation; solar radiation; relative humidity; and wind speed) at 938 sites in Japan and climate projections from the multi-model ensemble of global climate models (GCMs) used in the coupled model intercomparison project (CMIP3) and multi-model ensemble of regional climate models form the Japanese downscaling project (called S-5-3). The capability of the WGs to reproduce the statistical features of the observed data for the period 1981-2000 is assessed using several statistical tests and quantile-quantile plots. Overall performance of the WGs was good. The ELPIS-JP dataset consists of two types of daily data: (i) the transient scenarios throughout the twenty-first century using projections from 10 CMIP3 GCMs under three emission scenarios (A1B, A2 and B1) and (ii) the time-slice scenarios for the period 2081-2100 using projections from three S-5-3 regional climate models. The ELPIS-JP dataset is designed to be used in conjunction with process-based impact models (e.g. crop models) for assessment, not only the impacts of mean climate change but also the impacts of changes in climate variability, wet/dry spells and extreme events, as well as the uncertainty of future impacts associated with climate models and emission scenarios. The ELPIS-JP offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.