Rice research for food security and sustainable agricultural development in Asia: Achievements and future challenges

Rice is the major staple food of Asia, and an important source of employment and income in rural areas, particularly in low-income countries. Research has contributed significantly in achieving food security by increasing the yield potential of rice in irrigated systems, reducing the crop maturity period and achieving yield stability by developing resistance against major insects and diseases in the modern high-yielding varieties. Poverty is, however, still extensive in fragile rainfed rice ecosystems where rice yield has remained low, as scientists have yet to develop high-yielding varieties resistant to abiotic stresses and problem soils. Rice production needs to be increased by another 70% over the next 30 years to meet growing food needs. This has to be achieved with less land, less water, and less labor to accommodate the demand for these inputs from the expanding nonagricultural sectors. The challenge to the rice research community is to make further shifts in yield potential of rice for the irrigated systems, to close the yield gaps in the rainfed systems through developing resistance of high yielding varieties to abiotic stresses, and greater understanding of the interactions between genotypes and environment, developing durable resistance against pests and diseases to reduce farmers' dependence on harmful agrochemicals, and to increase efficiency in the use of water, labor and fertilizers. As further intensification of rice cultivation is inevitable, scientists must understand the negative environmental side-effects of increasing rice productivity, to develop appropriate mitigation options.     

Analysis of the positive ionospheric response to a moderate geomagnetic storm using a global numerical model

Current theories of F-layer storms are discussed using numerical simulations with the Upper Atmosphere Model, a global self-consistent, time dependent numerical model of the thermosphere-ionosphere-plasmasphere-magnetosphere system including electrodynamical coupling effects. A case study of a moderate geomagnetic storm at low solar activity during the northern winter solstice exemplifies the complex storm phenomena. The study focuses on positive ionospheric storm effects in relation to thermospheric disturbances in general and thermospheric composition changes in particular. It investigates the dynamical effects of both neutral meridional winds and electric fields caused by the disturbance dynamo effect. The penetration of short-time electric fields of magnetospheric origin during storm intensification phases is shown for the first time in this model study. Comparisons of the calculated thermospheric composition changes with satellite observations of AE-C and ESRO-4 during storm time show a good agreement. The empirical MSISE90 model, however, is less consistent with the simulations. It does not show the equatorward propagation of the disturbances and predicts that they have a gentler latitudinal gradient. Both theoretical and experimental data reveal that although the ratio of [O]/[N₂] at high latitudes decreases significantly during the magnetic storm compared with the quiet time level, at mid to low latitudes it does not increase (at fixed altitudes) above the quiet reference level. Meanwhile, the ionospheric storm is positive there. We conclude that the positive phase of the ionospheric storm is mainly due to uplifting of ionospheric F2-region plasma at mid latitudes and its equatorward movement at low latitudes along geomagnetic field lines caused by large-scale neutral wind circulation and the passage of travelling atmospheric disturbances (TADs). The calculated zonal electric field disturbances also help to create the positive ionospheric disturbances both at middle and low latitudes. Minor contributions arise from the general density enhancement of all constituents during geomagnetic storms, which favours ion production processes above ion losses at fixed height under day-light conditions.     

Growth, ionic and osmotic relations of an Allenrolfea occidentalis population in an inland salt playa of the Great Basin Desert

Variation in growth, physiology and ionic relations patterns of Allenrolfea occidentalis, a perennial halophyte of dry habitats, was studied under field conditions from May 1996 to November 1997. An A. occidentalis community has a characteristic soil pH of 7·3–8·3. During the two years, the population was exposed to great variations in soil salinity, from 29 to 146 dS m⁻¹, and soil moisture, ranging from drought (9·2%) to wet (19%). The salt concentrations were significantly higher in the surface soil layers than in the subsurface layers. Seasonal changes in dry weight are directly related to soil salinity stress. Allenrolfea occidentalis had greater growth and biomass production under saline conditions. Na⁺and Cl⁻ions were accumulated in plant tissues in much greater amounts than K⁺, Ca²⁺, and Mg²⁺. Soil salinities were significantly reduced at the end of the growing season. Water potentials of the shoots decreased significantly with increasing salinity. The plant (F_v/F_mratio) was more affected by salinity and irradiation levels during the summer period.     

RHESSI Microflares: II. Implications for Loop Structure and Evolution

We present simple analytic models which predict the peak X-ray emission measure and temperature attained in flares in which the chromospheric evaporation process takes place either in a single ‘monolithic’ loop or in a loop consisting of several filaments that are created successively as the energy release process proceeds in time. As possible mechanisms driving chromospheric evaporation we consider both classical heat conduction from the loop top and non-thermal electron beams. The model predictions are tested for a set of 18 well studied RHESSI microflares. The results suggest beam driven evaporation in filamented loops as being capable of accounting for the observed emission measures and temperatures though there are issues with the very high beam densities needed. On the other hand, estimates of the emission measures achieved by conductive evaporation which are derived by using the Rosner – Tucker – Vaiana (RTV) scaling law are much larger than the observed ones. Possible reasons for this discrepancy are discussed.     

Validation of an annual cycle simulation with a T42-L20 GCM

An annual cycle of an atmospheric general circulation model (AGCM) is presented. The winter and summer zonal averages of the atmospheric fields are compared with an observed climatology. The main features of the observed seasonal means are well reproduced by the model. One of the main discrepancies is that the simulated atmosphere is too cold, particularly in its upper part. Some other discrepancies might be explained by the interannual variability. The AGCM surface fluxes are directly compared to climatological estimates. On the other hand, the calculation of meridional heat transport by the ocean, inferred from the simulated energy budget, can be compared to transport induced from climatologies. The main result of this double comparison is that AGCM fluxes generally are within the range of climatological estimates. The main deficiency of the model is poor partitioning between solar and non-solar heat fluxes in the tropical belt. The meridional heat transport also reveals a significant energy-loss by the Northern Hemisphere ocean north of 45° N. The possible implications of model surface flux deficiencies on coupling with an oceanic model are discussed.This paper was presented at the International Conference on Modelling of Global Climate Change and Variability, held in Hamburg 11–15 September 1989 under the auspices of the Meteorological Institute of the University of Hamburg and the Max Planck Institute for Meteorology. Guest Editor for these papers is Dr. L. Dümenil     

Land cover classification by an artificial neural network with ancillary information

Abstract

Remote sensing is an important source of land cover data required by many GIS users. Land cover data are typically derived from remotely–sensed data through the application of a conventional statistical classification. Such classification techniques are not, however, always appropriate, particularly as they may make untenable assumptions about the data and their output is hard, comprising only the code of the most likely class of membership. Whilst some deviation from the assumptions may be tolerated and a fuzzy output may be derived, making more information on class membership properties available, alternative classification procedures are sometimes required. Artificial neural networks are an attractive alternative to the statistical classifiers and here one is used to derive a fuzzy classification output from a remotely–sensed data set that may be post–processed with ancillary data available in a GIS to increase the accuracy with which land cover may be mapped. With the aid ancillary information on soil type and prior knowledge of class occurrence the accuracy of an artificial neural network classification was increased by 29–93 to 77–37 per cent. An artificial neural network can therefore be used generate a fuzzy classification output that may be used with other data sets in a GIS, which may not have been available to the producer of the classification, to increase the accuracy with which land cover may be classified.     

First Data on the Isotopic Age of Zircons from Rocks of the Roseta Ultramafic Massif,Southern Margin of the São Francisco Craton (Brazil)

Doklady Earth Sciences - The results of isotope U–Pb dating of zircons from lherzolite and vein olivine orthopyroxenite composing the Roseta ultramafic massif are presented. The zircons...     

A portable extruder for accurate and precise high-resolution subsampling of unconsolidated sediment cores

Journal of Paleolimnology - We developed a portable extruder for precise and accurate high-resolution subsampling of unconsolidated sediment cores. This extruder is capable of producing subsamples...