Tamon Fumoto

Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2 ]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2 ] and temperature.

Combined emission of CH4 and N2O from a paddy field was reduced by preceding upland crop cultivation

Since crop rotation between paddy rice and upland crops is widely conducted in Japan and other Asian countries, the effect of crop rotation on greenhouse gas emission should be clarified. In this study, methane (CH4) and nitrous oxide (N2O) fluxes were simultaneously measured for two years from 2004 to 2005 in a paddy rice field with three different cultivation histories, i.e. consecutive paddy rice cultivation (PR), single cropping of upland rice (UR), and double cropping of soybean and wheat (SW) in the preceding two years from 2002 to 2003. In 2004, the cumulative CH4 emissions in the UR and SW plots were 511 and 2817 g CH4 m−2 y−1, which were 8 and 46%, respectively, of that in the PR plots (6092 g CH4 m−2 y−1). In 2005, the cumulative CH4 emissions in the UR and SW plots were 5123 and 1331 g CH4 m−2 y−1, which were 87 and 23%, respectively, of that in the PR plots (5893 g CH4 m−2 y−1), although the differences were not statistically significant. The soil reduction/oxidation potential (Eh) in the UR plots was higher than that in the PR plots in 2004. However, no distinctive differences in soil Eh among the three cropping systems were found in 2005. In the spring of 2004, the soil iron (Fe) content determined by extraction with dithionite-ethylenediaminetetraacetic acid (EDTA) solution was higher in the UR plots than in the PR and SW plots. However, no significant differences in Fe content among the three cropping systems were found in the spring of 2002 and 2005. The application of a relatively small amount of residue from the upland rice (c. 30% of that from the paddy rice) and the removal of all aboveground crop residues of soybean and wheat before paddy rice cultivation in 2004 could have contributed significantly to the low CH4 emissions in the UR and SW plots. In addition, change in the form of soil Fe during the preceding periods with upland crop cultivation may also have been related to the decreases in CH4 emission. The cumulative N2O emissions ranged from 39 to 99 mg N m−2 y−1, and showed no significant difference among the three cropping systems in 2004 and 2005. These results indicate that the combined CH4 and N2O emission from paddy soil is reduced by the introduction of the preceding upland crop cultivation when crop residue from the previous upland crop is small or removed before paddy rice cultivation, although this effect was expected only for one year just after the land use change from upland crop cultivation to paddy rice cultivation.

Validation of the DNDC-Rice model by using CH4 and N2O flux data from rice cultivated in pots under alternate wetting and drying irrigation management

The DNDC (DeNitrification-DeComposition)-Rice model, one of the most advanced process-based models for the estimation of greenhouse gas emissions from paddy fields, has been discussed mostly in terms of the reproducibility of observed methane (CH4) emissions from Japanese rice paddies, but the model has not yet been validated for tropical rice paddies under alternate wetting and drying (AWD) irrigation management, a water-saving technique. We validated the model by using CH4 and nitrous oxide (N2O) flux data from rice in pots cultivated under AWD irrigation management in a screen-house at the International Rice Research Institute (Los Baños, the Philippines). After minor modification and adjustment of the model to the experimental irrigation conditions, we calculated grain yield and straw production. The observed mean daily CH4 fluxes from the continuous flooding (CF) and AWD pots were 4.49 and 1.22 kg C ha−1 day−1, respectively, and the observed mean daily N2O fluxes from the pots were 0.105 and 34.1 g N ha−1 day−1, respectively. The root-mean-square errors, indicators of simulation error, of daily CH4 fluxes from CF and AWD pots were calculated as 1.76 and 1.86 kg C ha−1 day−1, respectively, and those of daily N2O fluxes were 2.23 and 124 g N ha−1 day−1, respectively. The simulated gross CH4 emissions for CF and AWD from the puddling stage (2 days before transplanting) to harvest (97 days after transplanting) were 417 and 126 kg C ha−1, respectively; these values were 9.8% lower and 0.76% higher, respectively, than the observed values. The simulated gross N2O emissions during the same period were 0.0279 and 1.45 kg N ha−1 for CF and AWD, respectively; these values were respectively 87% and 29% lower than the observed values. The observed total global warming potential (GWP) of AWD resulting from the CH4 and N2O emissions was approximately one-third of that in the CF treatment. The simulated GWPs of both CF and AWD were close to the observed values despite the discrepancy in N2O emissions, because N2O emissions contributed much less than CH4 emissions to the total GWP. These results suggest that the DNDC-Rice model can be used to estimate CH4 emission and total GWP from tropical paddy fields under both CF and AWD conditions.

Effects of Nitrogen Deposition on Nitrous Oxide Emissions from the Forest Floor

Increasing nitrogen deposition due to human activity might have a serious impact on ecosystem functions such as the nitrogen transformations conducted by microbes. We therefore focused on nitrous oxide (N2O) production as an indicator of soil microbial activity. The rates of N2O emission from the forest floor were measured every two weeks in two forest stands in the central part of Japan: a red pine stand at Kannondai and a deciduous stand at Yasato. Nitrogen deposition rates by throughfall were 30.6 kg N ha−1 y−1 at Kannondai and 15.7 at Yasato. The rates of N2O emission ranged from 0.5 to 14.2 µg N m−2 h−1 (mean 4.5) at Kannondai and from 0.2 to 7.0 µg N m−2 h−1 (mean 2.3) at Yasato. The N2O emission rate showed significant positive relationships with soil temperature and nitrogen deposition during the preceding two weeks. The annual emission rates of N2O were 0.38 kg N ha−1 y−1 at Kannondai and 0.20 at Yasato. As a the annual nitrogen deposition, these rates were 1.23% at Kannondai and 1.27% at Yasato.

Development of a method for estimating total CH4 emission from rice paddies in Japan using the DNDC-Rice model.

Methane (CH4) is a greenhouse gas, and paddy fields are one of its main anthropogenic emission sources. To mitigate this emission based on effective management measures, CH4 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 CH4 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 CH4 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 Japans 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 CH4 emission and organic carbon input rates. This suggests that the regressions provide a simplified method for estimating CH4 emission from Japanese paddy fields, though some modifications can further improve the estimation accuracy.

A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation

For most biophysical domains, differences in model structures are seldom quantified. Here, we used a taxonomy-based approach to characterise thirteen rice models. Classification keys and binary attributes for each key were identified, and models were categorised into five clusters using a binary similarity measure and the unweighted pair-group method with arithmetic mean. Principal component analysis was performed on model outputs at four sites. Results indicated that (i) differences in structure often resulted in similar predictions and (ii) similar structures can lead to large differences in model outputs. User subjectivity during calibration may have hidden expected relationships between model structure and behaviour. This explanation, if confirmed, highlights the need for shared protocols to reduce the degrees of freedom during calibration, and to limit, in turn, the risk that user subjectivity influences model performance. A taxonomy-based approach was used to classify AgMIP rice simulation models.Different model structures often resulted in similar outputs.Similar structures often led to large differences in outputs.User subjectivity likely hides relationships between model structure and behaviour.Shared protocols are still needed to limit the risks during calibration.

National-scale estimation of methane emission from paddy fields in Japan: Database construction and upscaling using a process-based biogeochemistry model

Abstract We have estimated methane (CH4) emission from total rice (Oryza sativa L.) paddies in Japan by means of a process-based biogeochemistry model, DeNitrification-DeComposition(DNDC)-Rice, combined with a geographic information system (GIS) database of climate, soil and farming practices. In the GIS database, 2 million ha of rice paddies were divided into 17,408 units according to 136 climate areas, 16 soil types, four classes of drainage rate and two classes of groundwater level, to simulate CH4 flux from each of the units applying the DNDC-Rice model. As a result, the national-scale CH4 emission in 1990 was estimated to be 216 Gg carbon (C), 13% lower than a previous inventory estimated by the Tier 2 method. By our Tier 3 approach, a relatively higher CH4 flux was estimated from eastern regions than from western regions of Japan, presumably due to the differences in climate and water management. Sensitivity analysis and uncertainty assessment indicated that it is important to account for the heterogeneity in soil properties such as field water capacity, iron (Fe) concentration and drainage rate, in order to reduce the uncertainty in regional estimates.

Causes of variation among rice models in yield response to CO2 examined with Free-Air CO2 Enrichment and growth chamber experiments

The CO2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO2] (E-[CO2]) by comparison to free-air CO2 enrichment (FACE) and chamber experiments. The model ensemble reproduced the experimental results well. However, yield prediction in response to E-[CO2] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO2] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO2] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice morphological development is conservative to carbon acquisition. Uncertainty will be reduced by incorporating this conservative nature of the morphological response to E-[CO2] into the models. Nitrogen levels, particularly under limited situations, make the prediction more uncertain. Improving models to account for [CO2] × N interactions is necessary to better evaluate management practices under climate change.

Prediction of future methane emission from irrigated rice paddies in central Thailand under different water management practices.

There is concern about positive feedbacks between climate change and methane (CH4) 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 CH4 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 CH4 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 CH4 emission well at each site. The simulated CH4 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 CH4 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 CH4 emission from irrigated rice paddies in central Thailand.

Estimation of Mineral Weathering Rates under Field Conditions Based on Base Cation Budget and Strontium Isotope Ratios

Base cation (BC) concentrations of rain, throughfall, percolation from leaf litter, and soil solution were periodically measured in two forests: Kannondai (red pine stand on volcanic soil) and Yasato (deciduous stands on granitic soil). Calculation of a BC budget gave the rate of BC release from soils; the BCs originated from mineral weathering and cation exchange. Weathering rates under field conditions were estimated from the Sr isotope ratios (87Sr/86Sr) of water and soil samples. Isotope ratios decreased in the order rain > throughfall > percolation > soil solution. Clay and silt had extremely high isotope ratios; this suggests that the sandy fraction, whose isotope ratio was smaller than that of the soil solution, was the main contributor to mineral weathering. Estimated BC weathering rates (kmolc-ha-1y-1) were 1.16 for Ca and 0.57 for Mg at Kannondai, and 0.82 for Ca and 0.51 for Mg at Yasato. The unexpected high weathering rate of granitic soil in Yasao was due to the wide coverage of the original parent material by volcanic ash. The contribution of cation exchange derived by subtraction was a little smaller than the weathering rates and was similar to the values estimated from a dynamic model that we developed.