Enhanced dissolution of arsenic in anaerobic soils upon organic amendment application: acid detergent-soluble organic matter as a potential indicator.

Application of organic amendments (OAMs) often enhances arsenic (As) dissolution in paddy soils. Therefore, understanding the properties of OAMs that determine the extent of As dissolution is essential for appropriate soil management. Since As dissolution increases with decrease in soil redox potential caused by microbial respiration, the decomposability of OAMs might be a critical factor controlling As dissolution in amended soils. We hypothesized that contents of acid detergent-soluble organic matter (ADSOM, mainly composed of non-fiber organic matter and hemicellulose) in OAMs can help estimate the potential of OAMs in accelerating As dissolution in soils with added OAMs. Therefore, two contrasting soil types, Andosol and Fluvisol, were mixed with 24 different OAMs and subjected to anaerobic incubation for 14 weeks. Changes in soil Eh and dissolved As contents were monitored throughout the incubation period, and As species in solid phases and ferrous iron (Fe(II)) contents in soils were measured after 2 and 6 weeks of incubation. The higher the ADSOM content in soils with OAMs, the higher the dissolved As contents in soils and the lower the Eh values. Dissolved As also positively correlated with the proportion of As(III) in solid phases and Fe(II) content after 2 and 6 weeks of incubation, indicating that decomposition of ADSOM led to reducing soil conditions, thereby promoting the reduction of As(V) and As-bearing Fe oxides and subsequent As dissolution. The results were consistent between the two types of soils, despite dissolved As content in the Andosol being two orders lower than that in Fluvisol. This is the first study to demonstrate that ADSOM can be a prominent indicator of the potential of OAMs, for promoting As dissolution, when applied to paddy soils.

Impacts of climate change on reproductive phenology in tropical rainforests of Southeast Asia.

In humid forests in Southeast Asia, many species from dozens of plant families flower gregariously and fruit synchronously at irregular multi-year intervals1-4. Little is known about how climate change will impact these community-wide mass reproductive events. Here, we perform a comprehensive analysis of reproductive phenology and its environmental drivers based on a monthly reproductive phenology record from 210 species in 41 families in Peninsular Malaysia. We find that the proportion of flowering and fruiting species decreased from 1976 to 2010. Using a phenology model, we find that 57% of species in the Dipterocarpaceae family respond to both drought and low-temperature cues for flowering. We show that low-temperature flowering cues will become less available in the future in the RCP2.6 and 8.5 scenarios, leading to decreased flowering opportunities of these species in a wide region from Thailand to the island of Borneo. Our results highlight the vulnerability of and variability in phenological responses across species in tropical ecosystems that differ from temperate and boreal biomes.

A Whole Leaf Comparative Study of Stomatal Conductance Models.

We employed a detailed whole leaf hydraulic model to study the local operation of three stomatal conductance models distributed on the scale of a whole leaf. We quantified the behavior of these models by examining the leaf-area distributions of photosynthesis, transpiration, stomatal conductance, and guard cell turgor pressure. We gauged the models' local responses to changes in environmental conditions of carbon dioxide concentration, relative humidity, and light irradiance. We found that a stomatal conductance model that includes mechanical processes dependent on local variables predicts a spatial variation of physiological activity across the leaf: the leaf functions of photosynthesis and transpiration are not uniformly operative even when external conditions are uniform. The gradient pattern of hydraulic pressure which is needed to produce transpiration from the whole leaf is derived from the gradient patterns of turgor pressures of guard cells and epidermal cells and consequently leads to nonuniform spatial distribution patterns of transpiration and photosynthesis via the mechanical stomatal model. Our simulation experiments, comparing the predictions of two versions of a mechanical stomatal conductance model, suggest that leaves exhibit a more complex spatial distribution pattern of both photosynthesis and transpiration rate and more complex dependencies on environmental conditions when a non-linear relationship between the stomatal aperture and guard cell and epidermal cell turgor pressures is implemented. Our model studies offer a deeper understanding of the mechanism of stomatal conductance and point to possible future experimental measurements seeking to quantify the spatial distributions of several physiological activities taking place over a whole leaf.

A pericycle-localized silicon transporter for efficient xylem loading in rice.

Rice is able to accumulate high concentrations of silicon (Si) in the shoots, and this ability is required for the mitigation of abiotic and biotic stresses. Although transporters for Si uptake have been identified, a transporter for the xylem loading of Si has not been found. We functionally characterized a Si transporter, OsLsi3, in terms of tissue-specific localization, knockout line phenotype and mathematic simulation. OsLsi3 was shown to be an efflux Si transporter. OsLsi3 was mainly expressed in the mature root region, and its expression was downregulated by Si. Immunostaining with a specific antibody showed that OsLsi3 was localized to the pericycle in the roots, without polarity. However, when it was expressed under the control of the OsLsi2 promoter, OsLsi3 became polarly localized to the proximal side of both the exodermis and endodermis. Knockout of this gene resulted in decreased Si uptake and concentration in the xylem sap under low Si supply, but not under high Si supply. Mathematical modeling showed that localization of OsLsi3 to the pericycle accounts for c. 30% of the total Si loading to the xylem under low Si concentrations. In summary, OsLsi3 was involved in the xylem loading of Si in rice roots, which is required for the efficient root-to-shoot translocation of Si.

On the Efficacy of Water Transport in Leaves. A Coupled Xylem-Phloem Model of Water and Solute Transport.

In this paper, we present and use a coupled xylem/phloem mathematical model of passive water and solute transport through a reticulated vascular system of an angiosperm leaf. We evaluate the effect of leaf width-to-length proportion and orientation of second-order veins on the indexes of water transport into the leaves and sucrose transport from the leaves. We found that the most important factor affecting the steady-state pattern of hydraulic pressure distribution in the xylem and solute concentration in the phloem was leaf shape: narrower/longer leaves are less efficient in convecting xylem water and phloem solutes than wider/shorter leaves under all conditions studied. The degree of efficiency of transport is greatly influenced by the orientation of second-order veins relative to the main vein for all leaf proportions considered; the dependence is non-monotonic with efficiency maximized when the angle is approximately 45° to the main vein, although the angle of peak efficiency depends on other conditions. The sensitivity of transport efficiency to vein orientation increases with increasing vein conductivity. The vein angle at which efficiency is maximum tended to be smaller (relative to the main vein direction) in narrower leaves. The results may help to explain, or at least contribute to our understanding of, the evolution of parallel vein systems in monocot leaves.

Extreme climate events increase risk of global food insecurity and adaptation needs.

Climate change is expected to increase the frequency, intensity and spatial extent of extreme climate events, and thus is a key concern for food production. However, food insecurity is usually analysed under a mean climate change state. Here we combine crop modelling and climate scenarios to estimate the effects of extreme climate events on future food insecurity. Relative to median-level climate change, we find that an additional 20-36% and 11-33% population may face hunger by 2050 under a once-per-100-yr extreme climate event under high and low emission scenarios, respectively. In some affected regions, such as South Asia, the amount of food required to offset such an effect is triple the region's current food reserves. Better-targeted food reserves and other adaptation measures could help fill the consumption gap in the face of extreme climate variability.

The Global Gridded Crop Model Intercomparison phase 1 simulation dataset.

The Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset of the Agricultural Model Intercomparison and Improvement Project (AgMIP) provides an unprecedentedly large dataset of crop model simulations covering the global ice-free land surface. The dataset consists of annual data fields at a spatial resolution of 0.5 arc-degree longitude and latitude. Fourteen crop modeling groups provided output for up to 11 historical input datasets spanning 1901 to 2012, and for up to three different management harmonization levels. Each group submitted data for up to 15 different crops and for up to 14 output variables. All simulations were conducted for purely rainfed and near-perfectly irrigated conditions on all land areas irrespective of whether the crop or irrigation system is currently used there. With the publication of the GGCMI phase 1 dataset we aim to promote further analyses and understanding of crop model performance, potential relationships between productivity and environmental impacts, and insights on how to further improve global gridded crop model frameworks. We describe dataset characteristics and individual model setup narratives.

State-of-the-art global models underestimate impacts from climate extremes.

Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.

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.

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

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.

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.

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.

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.