Masayuki Yokozawa

Future climate change, the agricultural water cycle, and agricultural production in China

Abstract Climate change would have a major impact on the hydrological cycle and consequently on available water resources, the potential for flood and drought, and agricultural productivity. In this study, the impacts of climate change on the agricultural water cycle and their implications for agricultural production in the 2020s were assessed by water-balance calculations for Chinese croplands. Temporal and spatial changes in potential evapotranspiration, actual evapotranspiration, soil-moisture, soil-moisture deficit, yield index, and cropland surface runoff under the baseline climate and a HADCM2 general circulation model (GCM) climate-change scenario were mapped on a grid of 0.5° latitude/longitude resolution. According to the analysis, agricultural water demand in south China is projected to decrease generally, and the cropland soil-moisture deficit would decrease due to climate change. However, in north China, agricultural water demand is expected to increase, and the soil-moisture deficit would increase generally. The changes in the water resources would have consequent impacts on the yield index. Cropland surface runoff during the growing period is expected to increase on some sloping croplands in the southwest mountain areas and in some areas along the south coast. These changes would have important implications for agricultural production. Particularly the rain-fed crops in the north China plain and northeast China would face water-related challenges in coming decades due to the expected increases in water demands and soil-moisture deficit, and decreases in precipitation.

Changes in agricultural water demands and soil moisture in China over the last half-century and their effects on agricultural production

It has become obvious in recent years that water is the most critical resource for Chinese agricultural ecosystems. Changes in agricultural water demands and soil moisture have significant implications for China’s water supply, the potential for drought and flood, and agricultural production. In the studies, we explored the changing trends in agricultural water demands, the changing trends and variability in soil moisture associated with both drought and increased surface runoff in Chinese croplands during the last half-century, and their impacts on agricultural production. We plotted temporal and spatial changes in agricultural water demands, soil moisture, soil-moisture variability, soil-moisture deficit, yield index, and surface runoff on a grid of 0.5 ◦ resolution. We found a trend toward agricultural water demands increasing, soil drying and significant changes in soil-moisture variability on the North China Plain and the Northeast China Plain. There was a significant decrease in agricultural water demands and a significant increase in soil-moisture levels in Southwest China, and a generally insignificant increase or decrease trend in agricultural water demands and soil-moisture levels in Southeast China. These changes in agricultural water demands and soil-moisture levels had corresponding impacts on soil-moisture deficit, and consequently on agricultural production. Increased surface runoff was found in the mountainous areas of the southwest and northeast, and in some areas along the South Coast.

Impacts of El Niño Southern Oscillation on the global yields of major crops

The monitoring and prediction of climate-induced variations in crop yields, production and export prices in major food-producing regions have become important to enable national governments in import-dependent countries to ensure supplies of affordable food for consumers. Although the El Niño/Southern Oscillation (ENSO) often affects seasonal temperature and precipitation, and thus crop yields in many regions, the overall impacts of ENSO on global yields are uncertain. Here we present a global map of the impacts of ENSO on the yields of major crops and quantify its impacts on their global-mean yield anomalies. Results show that El Niño likely improves the global-mean soybean yield by 2.1-5.4% but appears to change the yields of maize, rice and wheat by -4.3 to +0.8%. The global-mean yields of all four crops during La Niña years tend to be below normal (-4.5 to 0.0%). Our findings highlight the importance of ENSO to global crop production.

How to analyze long-term insect population dynamics under climate change: 50-year data of three insect pests in paddy fields

We can precisely predict the future dynamics of populations only if we know the underlying mechanism of population dynamics. Long-term data are important for the elucidation of such mechanisms. In this article we analyze the 50-year dynamics of annual light-trap catches of three insect pest species living in paddy fields in Japan: the rice stem borer, Chilo suppressalis (Walker) (Lepidoptera: Pyralidae); the green rice leafhopper, Nephotettix cincticeps (Uhler) (Hemiptera: Deltocephalidae); and the small brown planthopper, Laodelphax striatellus (Fallén) (Hemiptera: Delphacidae). We separate the long-term dynamics into two components by using locally weighted scatterplot smoothing: (1) the underlying dynamics of populations, and (2) the influence of the past changes in the environment. The former component is analyzed by response surface analysis and vector autoregression to evaluate the nonlinearity of density-dependence and the inter-specific influence of density, respectively. On the basis of these analyses, we perform the state-space model analyses. The state-space model selected by Akaike’s information criterion indicates that the observed number of light-trap catches of C. suppressalis and N. cincticeps in summer increases with increasing temperatures in the previous winter. It also indicates that the influence of temperature is not carried over to the next year. We utilize the selected model to predict the impact of global warming on these species, by substituting the temperature predicted by a general circulation model.

A chamber system with automatic opening and closing for continuously measuring soil respiration based on an open-flow dynamic method

We developed an automatic opening and closing chamber system (AOCC) based on an open-flow dynamic method (open-flow AOCC). The AOCC can be used during all four seasons, even at the surface of relatively deep snow. We compared the open-flow AOCC with two closed dynamic methods [the AOCC configured as a closed dynamic system (closed dynamic AOCC) and the LI-6400 system] under field conditions. The closed dynamic-AOCC and LI-6400 measurements were about 15.4% and 5.2% lower, respectively, than the values obtained with the open-flow AOCC. There was a significant difference in soil respiration rate between the open-flow AOCC and the closed dynamic AOCC system. In contrast, no significant difference in soil respiration rate was detected between the open-flow AOCC and the LI-6400 system. In the field, the open-flow AOCC permitted continuous long-term measurements under a range of temperature conditions and did a good job of reflecting the marked daily and seasonal variations in soil respiration as a function of soil temperature.

Use of the RothC model to estimate the carbon sequestration potential of organic matter application in Japanese arable soils

Abstract We estimated the carbon (C) sequestration potential of organic matter application in Japanese arable soils at a country scale by applying the Rothamsted carbon (RothC) model at a 1-km resolution. After establishing the baseline soil organic carbon (SOC) content for 1990, a 25-year simulation was run for four management scenarios: A (minimum organic matter application), B (farmyard manure application), C (double cropping for paddy fields) and D (both B and C). The total SOC decreased during the simulation in all four scenarios because the C input in all four scenarios was lower than that required to maintain the baseline 1990 SOC level. Scenario A resulted in the greatest depletion, reflecting the effects of increased organic matter application in the other scenarios. The 25-year difference in SOC accumulation between scenario A and scenarios B, C and D was 32.3, 11.1 and 43.4 Mt C, respectively. The annual SOC accumulation per unit area was similar to a previous estimate, and the 25-year averages were 0.30, 0.10 and 0.41 t C ha−1 year−1 for scenarios B, C and D, respectively. The system we developed in the present study, that is, linking the RothC model and soil spatial data, can be useful for estimating the potential C sequestration resulting from an increase in organic matter input to Japanese arable soils, although more feasible scenarios need to be developed to enable more realistic estimation.

Applying the Rothamsted Carbon Model for Long-Term Experiments on Japanese Paddy Soils and Modifying It by Simple Tuning of the Decomposition Rate

We applied the Rothamsted Carbon Model (RothC), which was developed for simulating the soil organic carbon (SOC) turnover in non-waterlogged soils, for long-term experiments (16–22 years) on Japanese paddy soils and modified it to accurately simulate the changes in the content of SOC with time in paddy soils. The RothC underestimated the SOC content in all the nine plots at five sites: Gley Soils in Akita and Shimane, Gray Lowland Soils in Toyama and Mie, and Yellow Soil in Oita prefecture. This may be mainly due to the slow decomposition rate of organic matter during the rice-growing season, when submerged soils are waterlogged and subjected to anaerobic conditions. On the other hand, the decomposition of organic matter might be inhibited, not only during the submergence period but also throughout the year in paddy soils because of the difference in the composition of microorganisms between upland and paddy soils. Taking these possibilities of differences in the decomposition rate between upland soils and paddy soils into account, we changed the decomposition rates of the RothC during the submergence period (summer) and the period without submergence (winter), separately. We ran the model many times by changing the decomposition rates for summer and winter separately and tried to identify the optimum combinations of the values of the factors required to change the default decomposition rate, so that the modeled SOC content would be consistent with the values observed in nine plots at five experimental sites. To determine the optimum combinations of the values of the factors, we used two statistical indices, the root mean square error (RMSE), which represents the degree of coincidence, and the mean difference (M), which is a measure of model bias. We found that the optimum combination of the values of the factors required to change the decomposition rate was 0.2 in summer and 0.6 in winter. The modified RothC for paddy soils by simple tuning of the decomposition rate using the values of the factors (0.2 and 0.6) resulted in a much better performance than that of the original RothC for simulating the changes in the SOC content with time in Japanese paddy soils under various climatic conditions, types of soil texture, and management systems. This modified model can be used for the estimation of carbon loss from soils as well as for the planning of suitable organic matter management, at least in Japanese paddy soils.

In silico simulation modeling reveals the importance of the casparian strip for efficient silicon uptake in rice roots

Silicon (Si) uptake by the roots is mediated by two different transporters, Lsi1 (passive) and Lsi2 (active), in rice (Oryza sativa). Both transporters are polarly localized in the plasma membranes of exodermal (outer) and endodermal (inner) cells with Casparian strips. However, it is unknown how rice is able to take up large amounts of Si compared with other plants, and why rice Si transporters have a characteristic cellular localization pattern. To answer these questions, we simulated Si uptake by rice roots by developing a mathematical model based on a simple diffusion equation that also accounts for active transport by Lsi2. In this model, we calibrated the model parameters using in vivo experimental data on the Si concentrations in the xylem sap and a Monte Carlo method. In our simulation experiments, we compared the Si uptake between roots with various transporter and Casparian strip locations and estimated the Si transport efficiency of roots with different localization patterns and quantities of the Lsi transporters. We found that the Si uptake by roots that lacked Casparian strips was lower than that of normal roots. This suggests that the double-layer structure of the Casparian strips is an important factor in the high Si uptake by rice. We also found that among various possible localization patterns, the most efficient one was that of the wild-type rice; this may explain the high Si uptake capacity of rice.

Effects of competition mode on spatial pattern dynamics in plant communities

Abstract The effects of the mode of competition between individual plants (symmetric versus asymmetric) and the gap formation caused by natural disturbances on the dynamics of spatial configuration pattern of individual size were investigated theoretically based on an individual growth model incorporating competitive effects of neighbouring individuals. The degree of spatial heterogeneity in local size distribution was represented by the CV (coefficient of variation) of averages of local size distributions (CVav), the average of CVs of local size distributions (AVcv) and the CV of CVs of local size distributions (CVcv). Without gap formation, CVav, AVcv and CVcv were larger under asymmetric competition than under symmetric one, suggesting a fine-scale mosaic spatial pattern in asymmetrically competing populations. With gap formation, these statistics under symmetric competition approached those values under asymmetric competition. The spatial configuration pattern of individual size also showed the same trend in terms of the semivariogram. The patchiness index was almost the same in both gap and non-gap cases irrespective of the mode of competition. The semivariogram and patchiness index showed the presence of more uniform and larger patches under symmetric competition than asymmetric competition. Gap formation therefore increased spatial heterogeneity in local size distribution especially under symmetric competition, but there was still a difference in spatial heterogeneity between the two modes of competition even in the gap formation case. The effects of gap formation on spatial pattern dynamics were larger under symmetric competition than under asymmetric competition; under asymmetric competition, the spatial pattern dynamics were similar in both gap and non-gap cases. Therefore, against spatial disturbances (i.e. gap formation), symmetric competition brings about a more variable system than asymmetric competition. These theoretical results can explain spatial pattern dynamics of natural forests (northern coniferous and temperate hardwood forests). In conclusion, both the disturbance regime (gap formation process) and the mode of competition between individuals should be investigated to study the spatial pattern dynamics and species diversity of plant communities. The implications of the mode of between-individual competition for conservation biology are discussed. It is suggested that symmetrically competing plant communities (e.g. northern coniferous forests) should be preserved in larger areas than asymmetrically competing ones (e.g. temperate hardwood forests) if the plant communities are subject to frequent natural disturbances.

How much has the increase in atmospheric CO2 directly affected past soybean production

Understanding the effects of climate change is vital for food security. Among the most important environmental impacts of climate change is the direct effect of increased atmospheric carbon dioxide concentration ([CO2]) on crop yields, known as the CO2 fertilization effect. Although several statistical studies have estimated past impacts of temperature and precipitation on crop yield at regional scales, the impact of past CO2 fertilization is not well known. We evaluated how soybean yields have been enhanced by historical atmospheric [CO2] increases in three major soybean-producing countries. The estimated average yields during 2002–2006 in the USA, Brazil, and China were 4.34%, 7.57%, and 5.10% larger, respectively, than the average yields estimated using the atmospheric [CO2] of 1980. Our results demonstrate the importance of considering atmospheric [CO2] increases in evaluations of the past effects of climate change on crop yields.