Gen Sakurai

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.

Forecasting flowering phenology under climate warming by modelling the regulatory dynamics of flowering-time genes

Understanding how climate warming has an impact on the life cycle schedule of terrestrial organisms is critical to evaluate ecosystem vulnerability to environmental change. Despite recent advances identifying the molecular basis of temperature responses, few studies have incorporated this knowledge into predictive models. Here we develop a method to forecast flowering phenology by modelling regulatory dynamics of key flowering-time genes in perennial life cycles. The model, parameterized by controlled laboratory experiments, accurately reproduces the seasonal changes in gene expression, the corresponding timing of floral initiation and return to vegetative growth after a period of flowering in complex natural environments. A striking scenario forecast by the model under climate warming is that the shift in the return time to vegetative growth is greater than that in floral initiation, which results in a significant reduction of the flowering period. Our study demonstrates the usefulness of gene expression assessment to predict unexplored risks of climate change.

Orchestration of three transporters and distinct vascular structures in node for intervascular transfer of silicon in rice

Significance Requirement of mineral elements differs with different organs and tissues; therefore, plants have developed systems for preferentially delivering mineral elements to tissues with high requirement. However, the molecular mechanisms for these systems are poorly understood. We took silicon (Si) as an example and revealed an efficient distribution system occurring in the node of rice, which is a hub for distribution. We found that hyperaccumulation of Si in the husk (more than 10%) is achieved by cooperation of three different Si transporters localized at the different cell layers in the node. Furthermore, mathematical modeling showed that an apoplastic barrier and development of enlarged vascular bundles are also required. Our work revealed a set of players for efficient distribution control in node. Requirement of mineral elements in different plant tissues is not often consistent with their transpiration rate; therefore, plants have developed systems for preferential distribution of mineral elements to the developing tissues with low transpiration. Here we took silicon (Si) as an example and revealed an efficient system for preferential distribution of Si in the node of rice (Oryza sativa). Rice is able to accumulate more than 10% Si of the dry weight in the husk, which is required for protecting the grains from water loss and pathogen infection. However, it has been unknown for a long time how this hyperaccumulation is achieved. We found that three transporters (Lsi2, Lsi3, and Lsi6) located at the node are involved in the intervascular transfer, which is required for the preferential distribution of Si. Lsi2 was polarly localized to the bundle sheath cell layer around the enlarged vascular bundles, which is next to the xylem transfer cell layer where Lsi6 is localized. Lsi3 was located in the parenchyma tissues between enlarged vascular bundles and diffuse vascular bundles. Similar to Lsi6, knockout of Lsi2 and Lsi3 also resulted in decreased distribution of Si to the panicles but increased Si to the flag leaf. Furthermore, we constructed a mathematical model for Si distribution and revealed that in addition to cooperation of three transporters, an apoplastic barrier localized at the bundle sheath cells and development of the enlarged vascular bundles in node are also required for the hyperaccumulation of Si in rice husk.

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.

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.

Dependency of parameter values of a crop model on the spatial scale of simulation

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.

Modeling irrigation‐based climate change adaptation in agriculture: Model development and evaluation in Northeast China

Replacing a rainfed cropping system with an irrigated one is widely assumed to be an effective measure for climate change adaptation. However, many agricultural impact studies have not necessarily accounted for the space-time variations in the water availability under changing climate and land use. Moreover, many hydrologic and agricultural assessments of climate change impacts are not fully integrated. To overcome this shortcoming, a tool that can simultaneously simulate the dynamic interactions between crop production and water resources in a watershed is essential. Here we propose the regional production and circulation coupled model (CROVER) by embedding the PRYSBI-2 (Process-based Regional Yield Simulator with Bayesian Inference version 2) large-area crop model into the global water resources model (called H08), and apply this model to the Songhua River watershed in Northeast China. The evaluation reveals that the models performance in capturing the major characteristics of historical change in surface soil moisture, river discharge, actual crop evapotranspiration, and soybean yield relative to the reference data during the interval 1979–2010 is satisfactory accurate. The simulation experiments using the model demonstrated that subregional irrigation management, such as designating the area to which irrigation is primarily applied, has measurable influences on the regional crop production in a drought year. This finding suggests that reassessing climate change risk in agriculture using this type of modeling is crucial not to overestimate potential of irrigation-based adaptation.

A Model of Silicon Dynamics in Rice: An Analysis of the Investment Efficiency of Si Transporters

Silicon is the second most abundant element in soils and is beneficial for plant growth. Although, the localizations and polarities of rice Si transporters have been elucidated, the mechanisms that control the expression of Si transporter genes and the functional reasons for controlling expression are not well-understood. We developed a new model that simulates the dynamics of Si in the whole plant in rice by considering Si transport in the roots, distribution at the nodes, and signaling substances controlling transporter gene expression. To investigate the functional reason for the diurnal variation of the expression level, we compared investment efficiencies (the amount of Si accumulated in the upper leaf divided by the total expression level of Si transporter genes) at different model settings. The model reproduced the gradual decrease and diurnal variation of the expression level of the transporter genes observed by previous experimental studies. The results of simulation experiments showed that a considerable reduction in the expression of Si transporter genes during the night increases investment efficiency. Our study suggests that rice has a system that maximizes the investment efficiency of Si uptake.

Inversely Estimating the Vertical Profile of the Soil CO2 Production Rate in a Deciduous Broadleaf Forest Using a Particle Filtering Method

Carbon dioxide (CO2) efflux from the soil surface, which is a major source of CO2 from terrestrial ecosystems, represents the total CO2 production at all soil depths. Although many studies have estimated the vertical profile of the CO2 production rate, one of the difficulties in estimating the vertical profile is measuring diffusion coefficients of CO2 at all soil depths in a nondestructive manner. In this study, we estimated the temporal variation in the vertical profile of the CO2 production rate using a data assimilation method, the particle filtering method, in which the diffusion coefficients of CO2 were simultaneously estimated. The CO2 concentrations at several soil depths and CO2 efflux from the soil surface (only during the snow-free period) were measured at two points in a broadleaf forest in Japan, and the data were assimilated into a simple model including a diffusion equation. We found that there were large variations in the pattern of the vertical profile of the CO2 production rate between experiment sites: the peak CO2 production rate was at soil depths around 10 cm during the snow-free period at one site, but the peak was at the soil surface at the other site. Using this method to estimate the CO2 production rate during snow-cover periods allowed us to estimate CO2 efflux during that period as well. We estimated that the CO2 efflux during the snow-cover period (about half the year) accounted for around 13% of the annual CO2 efflux at this site. Although the method proposed in this study does not ensure the validity of the estimated diffusion coefficients and CO2 production rates, the method enables us to more closely approach the “actual” values by decreasing the variance of the posterior distribution of the values.

Modeling Strategies for Plant Survival, Growth and Reproduction

Reproduction Akiko Satake*, Gen Sakurai and Toshinori Kinoshita* Faculty of Environmental Earth Science, Hokkaido University, N10W5, Kita-ku, Sapporo, 060-0810 Japan Ecosystem Informatics Division, National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba, 305-8604 Japan Division of Biological Science, Graduate School of Science, Nagoya University, Chikusa, Nagoya, 464-8602 Japan Institute of Transformative Bio-Molecules (WPI-ITbM), Nagoya University, Chikusa, Nagoya, 464-8602 Japan *Corresponding authors: Akiko Satake, E-mail, satake@ees.hokudai.ac.jp; Fax, +81-11-706-4954; Toshinori Kinoshita, E-mail, kinoshita@bio.nagoya-u.ac.jp; Fax, +81-52-789-4778.